generate_text
Write, summarize, compliance-check, retrieve, negotiate, translate, or define text with policy enforcement.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | ||
| input | Yes |
Write, summarize, compliance-check, retrieve, negotiate, translate, or define text with policy enforcement.
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | ||
| input | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure, but it only adds the vague phrase 'with policy enforcement' without specifying what policies are enforced, how they affect output, or side effects. There is no mention of safety, mutability, or task-specific behavior, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, reasonably concise and front-loaded with action verbs. However, 'policy enforcement' is vague and adds ambiguity without explanatory value, though it does not introduce waste or excessive length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple task types), the lack of annotations and output schema makes this description insufficient. It does not explain return values, policy behavior, differences between tasks, or task-specific input requirements, leaving the agent under-informed for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, so the description must compensate for parameter meaning. It repeats the enum values for 'task' but does not clarify what the 'input' parameter should contain for each task (e.g., a prompt for 'write', source text for 'translate'), nor does it explain the expected format or constraints beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description lists multiple text operations (write, summarize, compliance-check, retrieve, negotiate, translate, define) but lacks a single clear primary verb+resource, making it ambiguous what the tool's core function is. It also fails to differentiate from sibling tools like check_compliance and translate_word that cover overlapping tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use generate_text versus its siblings (e.g., when to choose this over check_compliance or translate_word). It merely lists capabilities without context, prerequisites, or exclusions, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clearly distinct purposes: dictionary lookups, reverse searches, translation, compliance checking, lesson generation, and knowledge graph exploration. The only ambiguity is generate_text, which overlaps with define_term and translate_word, but its role as a general text generation tool is clear from the description.
Naming is inconsistent, mixing verb_noun patterns (e.g., check_compliance, define_term, search_words) with get_* patterns (e.g., get_lesson, get_quiz) and the non-verb word_of_the_day. However, all names are descriptive and readable.
13 tools is well-scoped for a language platform covering dictionary, translation, lessons, quizzes, related words, images, and compliance. Each tool earns its place without redundancy or bloat.
The server provides comprehensive coverage for language-related workflows, including lookup, translation, lesson and quiz generation, related words, images, and compliance checks. Minor gaps like pronunciation audio or progress tracking exist, but core operations are well covered.